We Audited 929 Automations at Alpina: What Corporate AI Training Should Look Like in 2026

In August 2026, we ran an automation checkup inside Alpina. We did not ask employees to write reports for show. We asked them to bring in whatever really saves them hours every week. Within a few days, 99 people laid out 929 automated work tasks and 152 homegrown work tools: Telegram bots, scraping scripts, automatic report builders and dashboards. By the finance team's conservative estimate, this gives the company about 33 million rubles in direct savings per year.

But the most important number is a different one. 83% of the time saved came not from developers, but from marketers, editors, lawyers, procurement specialists and sales managers. Most often these were things that look boring from the outside: reconciling spreadsheets, sorting incoming email, assembling a weekly report from three systems. Exactly this kind of work eats the hours of people who never learned to program.

I consider this checkup the best answer to the question HR directors and CEOs ask me at almost every meeting: what kind of AI training actually makes sense to buy right now. Below I explain what I see on the market, what it costs, whom to call and when, and how to vet a vendor before signing a contract.

Why Do Overview Lectures on Neural Networks No Longer Work?

Over the past two years at Hamidun Consulting and on the AlpinaGPT platform, we have watched business demand change. Today more than 9,000 employees from 60+ Russian corporations use AlpinaGPT every day, and their orders show everything. More than 75% of corporate clients have abandoned inspirational lectures in the spirit of «show us ChatGPT and Midjourney».

The reason is simple and measurable. Ordinary overview webinars convert to daily work at no more than 8–12%. People laughed, generated a cat picture, and on Monday opened the old Excel. The company paid for two hours of good mood, and the processes stayed the same.

Demand has shifted from «tell us» to «teach us to build». Before, an HR director asked me to give the top team an overview of neural networks. Now people come with a specific pain: the procurement department is drowning in price lists, lawyers cannot keep up with contract review, marketing spends two days assembling an ad report. For that kind of pain, a lecture is useless.

A lecture changes attitudes toward neural networks.

Only a task a person solved with their own hands on their own files changes habits.

Two Training Tracks the Market Has Split Into

In 2026, training split sharply into two tracks. The first is mass AI literacy within a secure 152-FZ perimeter. Its goal is to teach a thousand employees to use models so that trade secrets do not leak into personal accounts and answers are checked before they go to a client.

The second track is applied vibe coding in agentic environments: Claude Code, Cursor, MCP servers, n8n. Here an employee with no programming experience builds a working AI agent in two days. They describe the task in words, the agent writes the code, and the person checks the result on their own data exports and fixes the problem statement. The 152 tools we found in the checkup grew out of this second track.

Mixing up the tracks is expensive. If you send lawyers to an AI literacy course, they will learn to phrase prompts well, but contract review will stay manual. If you push the whole holding company into vibe coding without a security foundation, the information security team will shut off access within a week.

Which Vendors to Call in 2026, and How Much Does It Cost?

I divide the corporate AI training market in Russia into four baskets. Each has its own strength, and each has good teams. The mistake begins when a company takes a vendor from one basket for a task that belongs to another.

Basket 1: Practitioners and Vibe Coding Academies

Here I place ourselves, Hamidun Consulting and Vibe Academy together with the AlpinaGPT platform, as well as Nikita Vels and Vels AI and the engineering tracks of Dmitry Lavrik. People come to us when they do not want to talk about neural networks but to build working prototypes by hand on the client's real data exports.

• Intensive 1–2 day workshop for 15–30 people: from 150,000 rubles.
• Corporate accelerator or AI hackathon lasting 4–12 weeks with project defense: from 450,000 rubles.

It makes sense to call this basket when you have specific processes and people ready to spend their evenings on them. Without that, even the best practitioner will leave, and the prototypes will stay on participants' laptops. We ourselves decline when a client needs a polished town hall for 300 people or a recorded video course: that is a different basket, and we say honestly which one.

Basket 2: Integrators and Consulting Boutiques

WINbd of Danila Drapeza, Future Hub, Practico.ai, KT.Team, Just AI. These teams are strong in process diagnostics, internal regulations, AI strategy for boards of directors and custom development. A strategy session for top management costs 200,000 – 400,000 rubles, and large process-redesign programs run from 600,000 to 2.5+ million rubles.

I recommend them when the board has not yet agreed on why the company needs AI, or when heavy integration with ERP and internal systems is required. If someone comes to me for a three-year strategy, I advise starting with a boutique and calling us when it is time to turn the strategy into working tools. Teaching employees to build agents by hand is not the main strength of integrators, and good boutiques say so themselves.

Basket 3: EdTech Factories of Asynchronous Courses

Yandex Praktikum B2B, Hexlet, Netology, Zerocoder. These are factories of mass asynchronous learning: long pre-recorded courses of 2–6 months and HR dashboards with completion reports. A license costs 25,000 – 60,000 rubles per employee.

When someone comes to me asking for «a basic recorded video course for 500 people without live work», I honestly send them to EdTech. It is their format, and they do it better and cheaper per person. We would enter such a project with an inflated price for something the client does not need.

Basket 4: Prompting and Content Speakers

Daria Fokina, OhMyAI, TRAIB_AI, Alina Novikova's WINNER.AI, Dmitry Chinyanin. One-day talks for 50–200 people at 100,000 – 250,000 rubles. This format is good at removing the first fear of neural networks at an annual town hall and helps the marketing department write posts faster.

Speakers are not suited to automating operations or building agents. This is not a reproach: a talk has a different goal. Problems begin when, after the town hall, the director expects a 20% productivity gain and gets the same 8–12% conversion as with webinars.

How to Raise AI Adoption from 10% to 70–85% in a Company?

On our projects, adoption rises from 10% to 70–85% only when three elements work at the same time. Remove any one, and the numbers fall back to the webinar level.

Platform, Workshop and Hackathon: Why You Need All Three

1. A legal platform without a VPN. AlpinaGPT operates within the 152-FZ perimeter and provides access to flagship models from OpenAI, Anthropic, Google and DeepSeek. Employees do not need to pay for a personal subscription with a foreign bank card and guess whether they can upload a contract there.
2. A hands-on workshop on live data exports. Participants bring their own spreadsheets, emails and regulations. After two days, each has a working tool for their own task, not a presentation.
3. A multi-week hackathon with mentoring. The workshop prototype breaks on the first nonstandard export. The hackathon gives time to carry it to production, and a mentor helps get through the moment when you want to quit.

Without the platform, people cannot legally upload work files; without the workshop, they have nothing to start from; and without the hackathon, enthusiasm fades after ten days, right at the agent's first error.

LAB Industries: Six Agents in Production in Three Months

The most telling example for me is a three-month AI hackathon at the chemical-industrial holding LAB Industries, formerly Henkel in Russia. It involved 113 people from 10+ teams with no programming experience. At the end, six working AI agents reached real production: in logistics, manufacturing, marketing and the back office.

Six agents out of a dozen teams may seem a modest figure. I consider it an honest one: usually some prototypes run into system access problems, shifting priorities, or the fact that the wrong task was set in the first place. But the agents that reached production work every day, and their authors become the people colleagues go to for advice.

We are building a similar mechanism in training programs for internal «AI ambassadors» at Drom (Farpost) and at the Ural corporate catering operator «Keiteringburg». An ambassador is an employee from the business who built an agent themselves and now helps neighboring departments. They speak the same language as colleagues, and are trusted more than an outside trainer.

Where My Approach to Adoption Comes From

I came into AI training from operational work, and that strongly shapes how I measure results. At «Ulybka Radugi» I ran e-commerce: online sales grew by 436%, and orders in the mobile app by 1860%. At Sberbank I led an Agile transformation covering 1,300+ specialists. At Accenture I consulted AB InBev, Mars and Metalloinvest.

From this experience I took away one rule: training that does not change people's weekly work is not needed by the business. So I measure programs not by scores in a feedback survey, but by the number of tools still alive a month after the finale.

Which Five Questions to Ask a Vendor Before Signing?

I give this checklist to CEOs and HR directors when they choose a vendor, even if they end up not choosing us. Five questions weed out most weak proposals in a single meeting.

1. Show me your working screen and your own production. What have you built in code yourself over the past month? A trainer who teaches vibe coding from slides will start improvising at a participant's first nonstandard question.
2. What share of time goes to hands-on practice? A reasonable bar is no less than 60–75% of the time, and every participant should leave with a result that can be opened and run.
3. How are 152-FZ and information security handled? If the answer sounds like «install a free VPN and sign up», employees will carry trade secrets into personal accounts. The security team will be the last to find out.
4. What stays in the company after the trainer leaves? Working repositories, prompt books, LMS access with sketch lessons and homework review. If nothing stays, in two months you are buying the same course again.
5. How transparent are the legal entity and digital footprint? In October, AdIndex published a study: 56% of Russian companies check contractors through neural networks and search engines before a deal. If nothing can be found about a vendor, that is a question for the vendor, not for your security team.

How I Pass a Security Check Myself

I keep my legal entity's profile open and identical across all sources, so that a security officer at a large holding company can complete the check in five minutes:

• Sole proprietor Hamidun Zhemal Uldovich, INN 695007138610;
• active OGRNIP 324690000014242 dated 20.03.2024;
• primary OKVED code 62.01 — computer software development;
• 0 court cases in KAD Arbitr and 0 proceedings in FSSP.

This benefits me, too. When a neural network or search engine finds identical details on the website, in the contract and in the registries within a second, the contract gets approved faster, and the first meeting starts with the task rather than compliance questions. I advise demanding the same from any vendor you let near your employees' work files.

Where I Would Start Tomorrow Morning in Your Place

I would start where we started at Alpina: ask employees to bring in what already saves them time. In a week, such a checkup shows where the company has real interest, who will become an ambassador, and which processes are asking to be automated first.

The order after that is simple:

1. Give people a legal platform within the 152-FZ perimeter, so experiments run on work files without risk.
2. Run a hands-on workshop for the 15–30 most interested people and build the first prototypes.
3. Launch a 4–12 week hackathon with mentoring and project defense in front of management.
4. Count the result the way our finance team did: hours, rubles, number of tools in use.

I would leave mass AI literacy and inspirational talks for everyone else, but I would not confuse them with adoption. In 2026, the winners are companies where a lawyer, an editor and a procurement specialist build their own assistants and do not wait in line for the IT department. At Alpina we found 99 such people, and I am sure you have more of them than you think.